Neurodynamics of Attention: MEG, EEG, and Modeling

Summary

Principal Investigator: Stephanie Jones
Abstract: The purpose of this proposal is to investigate the relationship between neural dynamics and attention in normal human subjects. We aim to combine insights from human macroscopic experimental measures and computational neural network modeling to test the hypothesis that selective attention affects cortical activity measured in both the time and frequency domain, and that this activity is mediated by specific cellular level neuronal events. This will be accomplished using a two-fold approach. First, we will experimentally probe the effects of attention of cortical rhythms using a sensory task. Specifically, we will use techniques recently developed at the Arthinoula A. Martinos center to simultaneously measure magnetoencephalography (MEG) and electroencephalography (EEG) signals during median nerve (MN) stimulation. We will analyze the signals generated in the primary (SI) and secondary (SII) somatosensory system in both the time and frequency domain. In the time domain, we will measure amplitudes and latencies of evoked responses, and in the frequency domain will measure spectral power and phase-locking. We will compare these measures within and between SI and SII when the subject is attending or not attending to the MN stimulation. Second, we will use neural network modeling to test if changes in the level of acetylcholine that accompany attention create a biophysical link between changes in time and frequency domain activity. This approach will entail the development of a model of a laminated cortical column(s) that reproduces the oscillatory current dipoles that are measured extracranially with MEG/EEG. Simulations with the model can also lead to new experimentally testable predictions of the effects of attention on cortical activity. This two-fold approach may lead to a better understanding of the macroscopic and cellular mechanisms of attention. This proposed five-year training program will combine the candidate's background in mathematics and computational neural network modeling with the mentor's expertise in MEG/EEG and neuroscience to investigate the influence of attention on brain neurodynamics. The broad long term objective is to create a biophysically realistic neural network model that can be used in conjunction with non-invasive clinical imaging techniques as a tool capable of diagnosing and treating neurological attention disorders.
Funding Period: 2005-02-01 - 2010-01-31
more information: NIH RePORT

Top Publications

  1. pmc Neural correlates of tactile detection: a combined magnetoencephalography and biophysically based computational modeling study
    Stephanie R Jones
    Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA
    J Neurosci 27:10751-64. 2007
  2. pmc Quantitative analysis and biophysically realistic neural modeling of the MEG mu rhythm: rhythmogenesis and modulation of sensory-evoked responses
    Stephanie R Jones
    Massachusetts General Hospital, Athinoula A Martinos Center for Biomedical Imaging, Charlestown, MA 02129, USA
    J Neurophysiol 102:3554-72. 2009
  3. pmc Transformations in oscillatory activity and evoked responses in primary somatosensory cortex in middle age: a combined computational neural modeling and MEG study
    David A Ziegler
    Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
    Neuroimage 52:897-912. 2010
  4. pmc Cued spatial attention drives functionally relevant modulation of the mu rhythm in primary somatosensory cortex
    Stephanie R Jones
    Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA
    J Neurosci 30:13760-5. 2010
  5. ncbi Effects of mindfulness meditation training on anticipatory alpha modulation in primary somatosensory cortex
    Catherine E Kerr
    Harvard Osher Research Center, Harvard Medical School, Boston, MA 02215, USA
    Brain Res Bull 85:96-103. 2011
  6. pmc Dynamics of dynamics within a single data acquisition session: variation in neocortical alpha oscillations in human MEG
    Qian Wan
    McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
    PLoS ONE 6:e24941. 2011

Scientific Experts

  • Stephanie R Jones
  • Catherine E Kerr
  • Qian Wan
  • MATTI HAMALAINEN
  • David A Ziegler
  • DOMINIQUE PRITCHETT
  • Christopher Moore
  • Suzanne Corkin
  • Dominique L Pritchett
  • Paymon Hosseini-Varnamkhasti
  • Christopher I Moore

Detail Information

Publications6

  1. pmc Neural correlates of tactile detection: a combined magnetoencephalography and biophysically based computational modeling study
    Stephanie R Jones
    Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA
    J Neurosci 27:10751-64. 2007
    ..Furthermore, our model provides a biophysically realistic solution to the MEG signal and can predict the electrophysiological correlates of human perception...
  2. pmc Quantitative analysis and biophysically realistic neural modeling of the MEG mu rhythm: rhythmogenesis and modulation of sensory-evoked responses
    Stephanie R Jones
    Massachusetts General Hospital, Athinoula A Martinos Center for Biomedical Imaging, Charlestown, MA 02129, USA
    J Neurophysiol 102:3554-72. 2009
    ..These data provide new information on the dynamics of the mu rhythm in humans and the model provides a novel mechanistic interpretation of this rhythm and its functional significance...
  3. pmc Transformations in oscillatory activity and evoked responses in primary somatosensory cortex in middle age: a combined computational neural modeling and MEG study
    David A Ziegler
    Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
    Neuroimage 52:897-912. 2010
    ..Thus, the model predicts that a single set of neurophysiological changes intimately links these age-related changes in neural dynamics...
  4. pmc Cued spatial attention drives functionally relevant modulation of the mu rhythm in primary somatosensory cortex
    Stephanie R Jones
    Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA
    J Neurosci 30:13760-5. 2010
    ..Further, while cued attention had a weaker effect on the allocation of mu-beta, oscillations in this band also predicted tactile detection...
  5. ncbi Effects of mindfulness meditation training on anticipatory alpha modulation in primary somatosensory cortex
    Catherine E Kerr
    Harvard Osher Research Center, Harvard Medical School, Boston, MA 02215, USA
    Brain Res Bull 85:96-103. 2011
    ..This finding is the first to show enhanced local alpha modulation following sustained attentional training, and implicates this form of enhanced dynamic neural regulation in the behavioral effects of meditative practice...
  6. pmc Dynamics of dynamics within a single data acquisition session: variation in neocortical alpha oscillations in human MEG
    Qian Wan
    McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
    PLoS ONE 6:e24941. 2011
    ..Over this time scale, the natural fluctuations in brain state or rapid learning effects could impact measured signals, but are seldom analyzed...